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InstantResearch.AI
Saving researchers' time and effort by finding highly relevant research papers.
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Table of Contents
About The Project
The project aims to address the problems associated with academic archive searches. Users often encounter subpar results due to biased ranking and outdated keyword search methods, which can bury relevant papers in deeper pages or exclude them from the results entirely. Additionally, users spend considerable time clicking on articles and attempting to understand their relevance.
Our solution leverages Cohere's semantic embeddings to reorganize search results, making them more relevant and accessible. We input the topic and research into our system, generate refined search criteria for the academic archive, and then query the site. The results are reordered using Cohere rerank and displayed to the user. Moreover, we provide a high-level summary of the selected articles to help users understand their content quickly. Additionally, we are using Anthrophic Claude API's to summarize the whole research paper.
This system also has potential applications in other domains such as patent filing, where it can find similar patents, and law, where it can identify relevant cases. It can even help in searching internal knowledge bases for pertinent information. This innovative solution is designed to make information search more efficient and effective.
Built With
App
Demo
Getting Started
To get a local copy up and running follow these simple example steps.
Prerequisites
Install the requirements with the following command.
pip install -r requirements.txt
Installation
Get the project running locally by following these steps.
- Get a Cohere API Key at https://cohere.com/
- Get a Anthropic Claude API Key at https://www.anthropic.com/
- Clone the repo
git clone https://github.com/JacobEverly/InstantResearch.AI.git
- Enter your Cohere API Key and Anthropic Claude API Key in a .streamlit file with
secrets.toml
.
cohere_key = <ENTER YOUR API KEY>
anthropic_key = <ENTER CLAUDE API KEY>
- Run the streamlit webapp.
streamlit run app.py
License
Distributed under the MIT License. See LICENSE.txt
for more information.
Contact
Rahul Jain, Jacob Everly, Sunil Sabnis, Nihar Shah, and Cooper McGuire
Project Link: https://github.com/JacobEverly/InstantResearch.AI
Acknowledgments
This project would not have been possible without the HackGPT hackathon organizing team.